Network Parameter Optimization for Customer Satisfaction
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Solution Overview
Problem
Current network systems struggle to optimize network parameters in real-time to enhance customer satisfaction, as existing methods are costly and unable to accurately measure satisfaction until customers switch providers, leading to delayed adjustments.
Innovation Solution
A system comprising a network probe, score generator, root-cause analyzer, and network optimizer that receives service type and key performance indicators to determine customer satisfaction scores and adjust network parameters, such as equipment manufacturer and signal strength, to improve satisfaction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If network equipment is continually upgraded to increase network speeds and reduce latency, then network performance is improved, but network expenses increase
Solution Approach 1:
The system changes network parameters (such as equipment manufacturer, signal strength, number of nodes) to optimize customer satisfaction without necessarily upgrading to more expensive equipment. By adjusting existing parameters and configurations, the system achieves improved network performance while controlling expenses.
Solution Approach 2:
The system automatically monitors customer satisfaction metrics and self-adjusts network parameters without requiring manual intervention or expensive infrastructure upgrades. The automated optimization process reduces the need for continuous equipment investments by intelligently managing existing network resources.
2Measurement precision
If customer satisfaction is measured only when customers drop service or switch carriers, then measurement cost is reduced, but satisfaction improvement timing is delayed
Solution Approach 1:
The system performs preliminary measurement of customer satisfaction indicators in real-time, before customers actually drop service or switch carriers. By proactively monitoring satisfaction metrics during the service relationship, the system can identify and address issues before customer churn occurs, enabling timely intervention.
Solution Approach 2:
The system implements continuous feedback loops that monitor customer satisfaction indicators and automatically adjust network parameters in real-time. This ongoing feedback mechanism allows the system to respond immediately to satisfaction changes rather than waiting for customer churn, creating a dynamic optimization process.
Data Source
AI summary
A method for optimizing network parameters of a network includes receiving, via a network probe in communication with the network, a service type, key performance indicators associated with the service type, and network parameter information of the network. A customer satisfaction score associated with the service type and the associated key performance indicators is determined. When the customer satisfaction score is determined to be below a threshold, one or more network parameters leading to the customer satisfaction score being below the threshold are determined from the network parameter information. The one or more network parameters are adjusted, via a network configuration interface in communication with the network, to thereby increase the customer satisfaction score.